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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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The basic mechanism for broadband shock noise in supersonic jets is the interaction between the shock waves and the turbulence in the jet exhaust. This source is in addition to jet mixing noise.
Advanced turbulence models are crucial for accurate prediction of rocket engine flows, due to existence of very large extra strain rates, such as strong streamline curvature. Numerical simulation of the turbulent flow in a strongly curved turn-around duct (TAD) has been carried out with a Reynolds stress model (RSM), an algebraic Reynolds stress model (ARSM) and a kappa-epsilon model. the RSM model and the ARSM model are found to capture the turbulence damping due to the convex curvature, but underpredict the turbulence enhancement caused by the concave curvature. To capture the concave curvature effects, it is necessary to modify the epsilon-equation. The modification of episilon-equation suggested by Launder, et.al, provides the correct trend, but over-corrects the curvature effects. A comparative study of two modes of transition in gas turbine, the by-pass transition and the separation-induced transition, has been carried out with several low-Reynolds-number (LRN) kappa-epsilon models. Effects of blade surface pressure gradient, freestream turbulence and Reynolds number on the blade boundary layer development, and particularly the inception of transition are examined in detail. The present study indicates that the turbine blade transition, in the presence of high freestream turbulence, is predicted well with LRN kappa-epsilon models employed.
The Inductive Monitoring System (IMS) software was developed to provide a technique to automatically produce health monitoring knowledge bases for systems that are either difficult to model (simulate) with a computer or which require computer models that are too complex to use for real time monitoring. IMS uses nominal data sets collected either directly from the system or from simulations to build a knowledge base that can be used to detect anomalous behavior in the system. Machine learning and data mining techniques are used to characterize typical system behavior by extracting general classes of nominal data from archived data sets. IMS is able to monitor the system by comparing real time operational data with these classes. We present a description of learning and monitoring method used by IMS and summarize some recent IMS results.
The purpose of this paper is to present an algorithm for using NonUniform Rational B-Spline (NURBS) representation in an aeroelastic loop. The algorithm is based on creating a least-squares NURBS surface representing the aeroelastic defection. The resulting NURBS surfaces are used to update either the original Computer- Aided Design (CAD) model, Computational Structural Mechanics (CSM) grid or the Computational Fluid Dynamics (CFD) grid. Results are presented for a generic High-Speed Civil Transport (HSCT).
Capillary phenomena plays an important role in the management of product water in PEM fuel cells because of the length scales associated with the porous layers and the gas flow channels. The distribution of liquid water within the network of gas flow channels can be dramatically altered by capillary flow. We experimentally demonstrate the rapid movement of significant volumes of liquid via capillarity through thin liquid films which connect orthogonal channels. The microfluidic experiments discussed provide a good benchmark against which the proper modeling of capillarity by computational models may be tested. The effect of surface wettability, as expressed through the contact angle, on capillary flow will also be discussed.
The Bay Area Environmental Research Institute (BAER) scientists have worked with the NASA Ames Research Center sunphotometer group led by Dr. Philip Russell for many years researching the climatic effects of aerosol particles in the stratosphere and troposphere. We have continued to work with the NASA Ames sunphotometer group in research activities representing funded, peer-reviewed proposals to NASA, NOAA and DOE. The activities are described in those proposals and also in the documents provided to the Grants Office earlier. This is the final report from January 1,2002 - June 30, 2005. The report consists of a compilation of 41 peer-reviewed publications (published, in press or submitted) produced under this Cooperative Agreement and 43 first-authored conference presentations. To save paper, reprints are not included but will, of course, be provided upon request.
Model-based reasoning is a powerful method for performing system monitoring and diagnosis. Building models for model-based reasoning is often a difficult and time consuming process. The Inductive Monitoring System (IMS) software was developed to provide a technique to automatically produce health monitoring knowledge bases for systems that are either difficult to model (simulate) with a computer or which require computer models that are too complex to use for real time monitoring. IMS processes nominal data sets collected either directly from the system or from simulations to build a knowledge base that can be used to detect anomalous behavior in the system. Machine learning and data mining techniques are used to characterize typical system behavior by extracting general classes of nominal data from archived data sets. In particular, a clustering algorithm forms groups of nominal values for sets of related parameters. This establishes constraints on those parameter values that should hold during nominal operation. During monitoring, IMS provides a statistically weighted measure of the deviation of current system behavior from the established normal baseline. If the deviation increases beyond the expected level, an anomaly is suspected, prompting further investigation by an operator or automated system. IMS has shown potential to be an effective, low cost technique to produce system monitoring capability for a variety of applications. We describe the training and system health monitoring techniques of IMS. We also present the application of IMS to a data set from the Space Shuttle Columbia STS-107 flight. IMS was able to detect an anomaly in the launch telemetry shortly after a foam impact damaged Columbia's thermal protection system.
The critical mission tasks assessments effort seeks to determine the physical performance requirements that astronauts must meet in order to safely and successfully accomplish lunar exploration missions. These assessments will determine astronaut preflight strength, fitness, and flexibility requirements, and the extent to which exercise and other countermeasures must prevent the physical deconditioning associated with prolonged weightlessness. The purpose is to determine the flexibility and strength that crewmembers must possess in order to reach Crew Exploration Vehicle controls during maneuvers that result in sustained acceleration levels ranging from 3.7G to 7.8G. An industry standard multibody dynamics application was used to create human models representing a 5th percentile female, a 50th percentile male, and a 95th percentile male. The additional mass of a space suit sleeve was added to the reaching arm to account for the influence of the suit mass on the reaching effort. The human model was merged with computer models of a pilot seat and control panel for the Crew Exploration Vehicle. Three dimensional paths were created that guided the human models hand from a starting position alongside its thigh to three control targets: a joystick, a keyboard, and an overhead switch panel. The reaching motion to each target was repeated under four vehicle acceleration conditions: nominal ascent (3.7G), two ascent aborts (5.5G and 7.8G) and lunar reentry (4.6G). Elbow and shoulder joint angular excursions were analyzed to assess range of motion requirements. Mean and peak elbow and shoulder joint torques were determined and converted to equivalent resistive exercise loads to assess strength requirements. Angular excursions for the 50th and 95th percentile male models remained within joint range of motion limits. For the 5th percentile female, both the elbow and the shoulder exceeded range of motion limits during the overhead reach. Elbow joint torques ranged from 10 N-m (nominal ascent) to 60 N-m (ascent abort). Shoulder joint torques ranged from 65 N-m (nominal ascent) to 280 N-m (ascent abort). Maximal equivalent exercise loads reached 30 lb in tricep extension, 9 lb in bicep curl, 110 lb in unilateral pullover and unilateral bench press for nominal conditions (lunar reentry), and 188 lb in unilateral pullover and unilateral bench press. The location of the pilot seat was found to be inadequately located to allow a 5th percentile female to reach the switches on the overhead panel. Elbow strength requirements were found to be well within population norms. Shoulder strength was found to be a limiting factor. Reaching under nominal ascent and lunar reentry conditions was found to require near maximal shoulder strength. Reaching under ascent abort conditions requires shoulder strength well beyond population norms. Pilot seats must adjust to accomodate a 5th percentile female. Exercise countermeasures must maintain maximal pullover and bench press strength to allow pilots to reach and operate controls during lunar reentry. Reaching will not be possible during ascent abort conditions. Flight controls should be built into armrests or flight control must be accomplished by autonomous systems during acceleration exceeding 4.6G.
A method of simulating operation of a VLSI interconnect structure having capacitive and inductive coupling between nodes thereof. A matrix X and a matrix Y containing different combinations of passive circuit element values for the interconnect structure are obtained where the element values for each matrix include inductance L and inverse capacitance P. An adjacency matrix A associated with the interconnect structure is obtained. Numerical integration is used to solve first and second equations, each including as a factor the product of the inverse matrix X.sup.1 and at least one other matrix, with first equation including X.sup.1Y, X.sup.1A, and X.sup.1P, and the second equation including X.sup.1A and X.sup.1P.
The high charge and high energy (HZE) particle radiation environment in space interacts with spacecraft materials and the human body to create a population of neutrons encompassing a broad kinetic energy spectrum. As an HZE ion penetrates matter, there is an increasing chance of fragmentation as penetration depth increases. When an ion fragments, secondary neutrons are released with velocities up to that of the primary ion, giving some neutrons very long penetration ranges. These secondary neutrons have a high relative biological effectiveness, are difficult to effectively shield, and can cause more biological damage than the primary ions in some scenarios. Ground-based irradiation experiments that simulate the space radiation environment must account for this spectrum of neutrons. Using the Particle and Heavy Ion Transport Code System (PHITS), it is possible to simulate a neutron environment that is characteristic of that found in spaceflight. Considering neutron dosimetry, the focus lies on the broad spectrum of recoil protons that are produced in biological targets. In a biological target, dose at a certain penetration depth is primarily dependent upon recoil proton tracks. The PHITS code can be used to simulate a broad-energy neutron spectrum traversing biological targets, and it account for the recoil particle population. This project focuses on modeling a neutron beamline irradiation scenario for determining dose at increasing depth in water targets. Energy-deposition events and particle fluence can be simulated by establishing cross-sectional scoring routines at different depths in a target. This type of model is useful for correlating theoretical data with actual beamline radiobiology experiments. Other work exposed human fibroblast cells to a high-energy neutron source to study micronuclei induction in cells at increasing depth behind water shielding. Those findings provide supporting data describing dose vs. depth across a water-equivalent medium. This poster presents PHITS data suggesting an increase in dose, up to roughly 10 cm depth, followed by a continual decrease as neutrons come to a stop in the target.
A method of simulating operation of a VLSI interconnect structure having capacitive and inductive coupling between nodes thereof. A matrix X and a matrix Y containing different combinations of passive circuit element values for the interconnect structure are obtained where the element values for each matrix include inductance L and inverse capacitance P. An adjacency matrix A associated with the interconnect structure is obtained. Numerical integration is used to solve first and second equations, each including as a factor the product of the inverse matrix X.sup.-1 and at least one other matrix, with first equation including X.sup.-1Y, X.sup.-1A, and X.sup.-1P, and the second equation including X.sup.-1A and X.sup.-1P.
No abstract available
A system for simulating operation of a VLSI interconnect structure having capacitive and inductive coupling between nodes thereof, including a processor, and a memory, the processor configured to perform obtaining a matrix X and a matrix Y containing different combinations of passive circuit element values for the interconnect structure, the element values for each matrix including inductance L and inverse capacitance P, obtaining an adjacency matrix A associated with the interconnect structure, storing the matrices X, Y, and A in the memory, and performing numerical integration to solve first and second equations.
No abstract available
In this CIF we worked to develop quantum algorithms for material science simulations based on new ideas recently proposed on plane wave basis sets. Many body simulations are not generally performed in plane wave basis sets on classical hardware, but with newly proposed quantum algorithms, it is possible this will be a highly efficient basis set to run quantum simulations on quantum hardware. Using state of the art classical simulations we ran small test simulations to estimate the resources that will be needed to run such plane wave algorithms on quantum hardware. We demonstrate our approach for a series of atoms and molecular systems.